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Foundational Python for Data Science

Jezik EngleskiEngleski
Knjiga Meki uvez
Knjiga Foundational Python for Data Science Kennedy Behrman
Libristo kod: 33499079
Nakladnici ADDISON WESLEY PUB CO INC, listopad 2021
Data science and machine learning—two of the world''s hottest fields—are attracting talent from a w... Cijeli opis
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Data science and machine learning—two of the world''s hottest fields—are attracting talent from a wide variety of technical, business, and liberal arts disciplines. Python, the world''s #1 programming language, is also the most popular language for data science and machine learning. This is the first guide specifically designed to help students with widely diverse backgrounds learn foundational Python so they can use it for data science and machine learning. This book is catered to introductory-level college courses on data science. 


Leading data science instructor and practitioner Kennedy Behrman first walks through the process of learning to code for the first time with Python and Jupyter notebook, then introduces key libraries every Python data science programmer needs to master. Once students have learned these foundations, Behrman introduces intermediate and applied Python techniques for real-world problem-solving. Throughout, Foundational Python for Data Science presents hands-on exercises, learning assessments, case studies, and more—all created with Colab (Jupyter compatible) notebooks, so students can execute all coding examples interactively without installing or configuring any software.

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Informacije o knjizi

Puni naziv Foundational Python for Data Science
Autor Kennedy Behrman
Jezik Engleski
Uvez Knjiga - Meki uvez
Datum izdanja 2021
Broj stranica 256
EAN 9780136624356
ISBN 0136624359
Libristo kod 33499079
Nakladnici ADDISON WESLEY PUB CO INC
Težina 408
Dimenzije 178 x 229 x 13

Kategorija

Computing & Information Technology > Computer programming / software engineering > Programming & scripting languages: general
Computing & Information Technology > Databases > Data warehousing
Computing & Information Technology > Databases > Data mining
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